It has been shown in [P. Ekstrand, “Bandwidth extension of audio signals by spectral band replication”, Proc. 1st IEEE Benelux Workshop on Model based Processing and Coding of Audio (MPCA-2002), pp. 53-58, Leuven, Belgium, 2002], that a complex-exponential modulated filter bank is an excellent tool for spectral envelope adjustment of audio signals. One application of this feature is audio coding based on Spectral Band Replication (SBR). Other fruitful applications of a complex filter bank include frequency selective panning and spatialization for parametric stereo, see [E. Schuijers, J. Breebart, H. Purnhagen, J. EngdegArd: “Low complexity parametric stereo coding”, Proc. 116th AES convention, 2004, paper 6073] and parametric multichannel coding, see [J. Herre et al.: “The reference model architecture for MPEG spatial audio coding”, Proc. 118th AES convention, 2005, paper 6447]. In those applications the frequency resolution of the complex filter bank is further enhanced at low frequencies by means of sub-subband filtering. The combined hybrid filter bank hereby achieves a frequency resolution that enables the processing of spatial cues at a spectral resolution which closely follows the spectral resolution of the binaural auditory system.
In some applications, however, the resolution of the filter bank is still insufficient, in the sense that simple gain modifications in each subband do not suffice to truthfully model the action of a given filter. For binaural rendering of multi-channel audio by means of HRTF (head related transfer function) related filtering, the intricate phase characteristics of the filters are important for the perceived audio quality. It is of course possible to apply fast convolution methods based on the DFT (Discrete Fourier Transform) as a post-process to the multi-channel rendering, but if the rendering device already contains the signals in the subband domain of complex exponential modulated filter bank, there are significant advantages in terms of computational complexity and algorithmic integration in performing the HRTF derived filtering in the subband domain, which will be outlined in more detail later. Since HRTF's are different for each individual and the derived filters depend on virtual source and/or listener positions which can for instance be changed by control signals, user interfaces or by other description signals, it is also important to be able to efficiently convert a given HRTF related filter into subband domain filters.
It is therefore the object of the present invention to provide a filter apparatus for filtering a time domain input signal, a method for filtering a time domain input signal, a filter generator or a method for providing an intermediate filter definition signal, which allow a more efficient or a more flexible manipulation of a time domain input signal with a better quality.
This object is achieved by a filter apparatus according to claim 1, by a method for filtering a time domain input signal according to claim 41, a filter generator according to claim 25, a method for providing an intermediate filter definition according to claim 42, a system according to claim 40, a computer program according to claim 43 or a computer program according to claim 44.